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Tail movement is an important component of vertebrate locomotion and likely contributes to dynamic stability during steady-state locomotion. Previous results suggest that the tail plays a significant role in lizard locomotion, but little data are available on tail motion during locomotion and how it differs with morphological, ecological, and phylogenetic parameters. We collected high-speed vertical climbing and horizontal locomotion video data from 43 lizard species from four taxonomic groups (Agamidae, Gekkota, Scincidae, and Varanidae) across four habitats. We introduce a new semi-automated and generalizable analysis pipeline for tail and spine motion analysis including markerless pose-estimation, semi-automated kinematic recognition, and muti-species data analysis. We found that step length relative to snout-vent length (SVL) increased with tail length relative to SVL. Examining spine cycles agnostic to limb stride phase, we found that ranges of inter-tail bending compared with inter-spine bending increased with relative tail length, while ranges of tail deflection relative to spine deflection increased with relative speed. Considering stepwise strides, we found the angular velocity and acceleration of the tail center of mass increased with relative speed. These results will provide general insights into the biomechanics of tails in sprawling locomotion enabling biomimetic applications in robotics, and a better understanding of vertebrate form and function. We look forward to adding more species, behaviors, and locomotor speeds to our analysis pipeline through collaboration with other research groups.
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http://dx.doi.org/10.1093/icb/icab037 | DOI Listing |
Med Biol Eng Comput
September 2025
Department of Computer Science, Università degli Studi di Bari Aldo Moro, Bari, Italy.
Fetal standard plane detection is essential in prenatal care, enabling accurate assessment of fetal development and early identification of potential anomalies. Despite significant advancements in machine learning (ML) in this domain, its integration into clinical workflows remains limited-primarily due to the lack of standardized, end-to-end operational frameworks. To address this gap, we introduce FetalMLOps, the first comprehensive MLOps framework specifically designed for fetal ultrasound imaging.
View Article and Find Full Text PDFOsteoarthr Cartil Open
December 2025
Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region of China.
Objective: We developed and validated an artificial intelligence pipeline that leverages diffusion models to enhance prognostic assessment of knee osteoarthritis (OA) by analyzing longitudinal changes in patella shape on lateral knee radiographs.
Method: In this retrospective study of 2,913 participants from the Multicenter Osteoarthritis Study, left-knee weight-bearing lateral radiographs obtained at baseline and 60 months were analyzed. Our pipeline commences with an automatic segmentation for patella shapes, followed by a diffusion model to predict patella shape trajectories over 60 months.
JAMIA Open
October 2025
Applied Clinical Research Center, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States.
Objective: To develop a natural language processing (NLP) pipeline for unstructured electronic health record (EHR) data to identify symptoms and functional impacts associated with Long COVID in children.
Materials And Methods: We analyzed 48 287 outpatient progress notes from 10 618 pediatric patients from 12 institutions. We evaluated notes obtained 28 to 179 days after a COVID-19 diagnosis or positive test.
ACS Omega
September 2025
Division of Pharmaceutical Chemistry, Faculty of Pharmaceutical Sciences, Khon Kaen University, Khon Kaen 40002, Thailand.
Dengue virus remains a significant global health threat, imposing a substantial disease burden on nearly half of the world's population. The urgent need for effective antiviral therapeutics, including therapeutic peptides targeting the Dengue virus, is critical in the current healthcare landscape. However, the availability of anti-Dengue peptides (ADPs) data remains limited in existing data sets, posing a challenge for computational modeling and discovery.
View Article and Find Full Text PDFNAR Genom Bioinform
September 2025
[This corrects the article DOI: 10.1093/nar/lqaf063.].
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